• Fine-tuning of SLMs tailored to specific needs • Implementation of agents and integrations as required • Implementation of multi-LLM routing • Preparation of technical and business documentation • Knowledge transfer • Conduct cost–benefit analysis.

Role Description Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy – fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. - Lead data center from early-stage opportunity through Ready-to-Build and energisation - Assess sites from technical, planning, power, and infrastructure perspectives - Develop grid connection and power strategies with National Grid, DNOs, and utility providers - Support planning, permitting, and stakeholder engagement processes - Identify and mitigate technical and development risks - Ensure projects are deliverable, scalable, and aligned with construction requirements - Experience developing data centers or large-scale infrastructure projects - Strong technical understanding of data center infrastructure, including power, cooling, and utility systems, with the ability to evaluate engineering decisions and challenge technical assumptions - Strong understanding of AUS planning and grid connection processes - Experience taking projects from early-stage development through design, permitting, and delivery readiness - Highly analytical, self-directed, and comfortable with significant ownership Qualifications - Experience developing data centers or large-scale infrastructure projects - Strong technical understanding of data center infrastructure, including power, cooling, and utility systems - Strong understanding of AUS planning and grid connection processes - Experience taking projects from early-stage development through design, permitting, and delivery readiness - Highly analytical, self-directed, and comfortable with significant ownership Requirements - Lead data center from early-stage opportunity through Ready-to-Build and energisation - Assess sites from technical, planning, power, and infrastructure perspectives - Develop grid connection and power strategies with National Grid, DNOs, and utility providers - Support planning, permitting, and stakeholder engagement processes - Identify and mitigate technical and development risks - Ensure projects are deliverable, scalable, and aligned with construction requirements Benefits - Competitive salary - Biannual bonus scheme - Fully expensed tech to match your needs

• Design, build, and debug the highest-impact pipelines, connecting our business systems, including CRM, billing, and internal platforms to our Snowflake warehouse, in both directions • Own the data strategy and architecture across a multi-year horizon, while maintaining deep, hands-on familiarity with the systems and their edge cases • Establish technical direction and standards for pipeline design, data modeling, and data quality across the org; personally build and ship the highest-risk or most ambiguous work • Build, structure, and lead a growing Data organization of 5+ across Data Engineering, ML Engineering, and Analytics • Own headcount planning, hiring strategy, and budget for the Data organization • Partner with the Chief Product and Technology Officer and cross-functional leaders to translate company strategy into data contracts and platform investments • Lead audits of existing integrations and automations, and determine what should be replaced and how that work should be prioritized • Champion AI and automation enablement company-wide, ensuring agents and LLM use cases are built on a trusted data foundation, while remaining hands-on in building select enablement capabilities

• Conduct comprehensive gap analysis and data mapping across 80+ ERP systems to identify integration challenges, data inconsistencies, and transformation requirements. • Design and develop standardized ETL pipelines and data transformation processes for migrating enterprise data into Microsoft Fabric. • Build robust data quality frameworks and validation rules to ensure data readiness for AI and analytics workloads. • Lead hands-on implementation of ETL standards and best practices, establishing repeatable patterns and automation scripts for multi-source integrations. • Develop and optimize data models that support seamless transformation from fragmented ERP sources into a unified, AI-ready data architecture. • Lead the pilot implementation phase, testing and refining standards against real ERP data before full-scale rollout. • Mentor and guide team members on ETL development, data transformation techniques, and Fabric-specific engineering practices. • Collaborate with stakeholders to document data lineage, transformation logic, and integration patterns for knowledge transfer and governance. • Troubleshoot data inconsistencies and implement corrective measures to maintain data integrity throughout the pipeline.